The present invention relates to hyper-spectral imaging and analysis of a sample of matter, and more particularly, to a method for hyper-spectral imaging and analysis of a sample of matter, for identifying and characterizing an object of interest therein. The present invention includes a procedure for preparing a test solution or suspension from a sample of matter, such that the test solution or suspension is particularly suitable for subjecting to hyper-spectral imaging and analysis. The present invention is generally applicable for on-line (e.g., real time or near-real time) or off-line hyper-spectral imaging and analysis of various different types or kinds of samples of matter, wherein the matter, and at least one object of interest therein, are composed or made up of organic or/and inorganic materials or substances, which are in a solid (e.g., particulate) phase, a liquid (e.g., solution or suspension) phase, or/and a gaseous (e.g., aerosol) phase. The present invention provides the capability of achieving the ‘ultimate’ combination of the highly desirable performance parameters of high accuracy, ‘and’ high precision (high reproducibility), ‘and’ high resolution, ‘and’ high sensitivity, and at high speed (short time scale), all at the same time (i.e., simultaneously), be it during on-line or off-line, in an optimum and highly efficient manner.
An exemplary specific application of the present invention involves on-line (real time or near-real time) or off-line hyper-spectral imaging and analysis of a sample of air (i.e., an air sample), for identifying and characterizing an object of interest therein, wherein the object of interest is a (potentially hazardous) biological agent or a (potentially hazardous) chemical agent. In general, the object of interest (i.e., biological agent or chemical agent) in the air sample is composed or made up of organic or/and inorganic materials or substances, which are in a solid (e.g., particulate) phase, a liquid (e.g., solution or suspension) phase, or/and a gaseous (e.g., aerosol) phase. Preferably, the object of interest (i.e., biological agent or chemical agent) in the air sample is composed or made up of organic or/and inorganic materials or substances, which are in a particulate form solid phase or/and are present (e.g., absorbed or/and adsorbed) on particles of the air sample. The sample of air is collected or obtained (e.g., via a standard type of air sampling or collecting system) from an indoor source of air (e.g., a post office, an airport, a subway station, a shopping mall, a sports arena, or an office building), or from an outdoor source of air. Exemplary biological agents are bacteria, viruses, fungi, and toxins. Exemplary chemical agents are nerve agents (e.g., sarin, tabun, and soman), and chemical poisons (e.g., cyanide compounds, and organophosphate compounds). The object of interest can be a biological agent, such as the (extremely hazardous) spore-forming bacterium Bacillus anthracis, which is chemically marked (e.g., via terbium trichloride [TbCl3]), or biologically marked (e.g., via antibodies of an immunoassay technique), as part of the main step (procedure) of preparing a test solution or suspension of the sample of matter, i.e., the air sample, for enabling identification and characterization thereof via hyper-spectral imaging and analysis.
Sample of Matter
A sample of matter generally refers to a relatively small quantity of matter which is representative of, and an example of, (i.e., a sample), of a relatively large, quantity of the matter, where matter generally refers to something (i.e., entity, material, substance) that has mass, occupies volume, and exists as a solid, liquid, gas, or a combination thereof. A sample of matter may also be considered as being a specimen (i.e., example) of the matter. Herein, the term ‘object’ generally refers to, and is considered equivalent to, and synonymous with, at least part of a given matter, and therefore, that which is present in a sample of the matter. Accordingly, the term ‘object’ generally refers to, and is considered equivalent to, and synonymous with, at least part of something (i.e., entity, material, substance) that has mass, occupies volume, and exists as a solid, liquid, gas, or a combination thereof, and therefore, that which is present in a sample of matter. Moreover, each object (i.e., at least part of a given matter) is definable and characterizable by a set of a wide variety of numerous possible biological, chemical, or/and physical, properties, characteristics, and behavior.
Analyzing a Sample of Matter
In essentially every field or area of science and technology there are applications which are based on, or involve, the need for on-line (real time or near-real time) or off-line analyzing a sample of matter, for a main purpose or objective of identifying and characterizing at least one object (i.e., entity, material, substance) of interest, usually among a variety of different types or kinds of objects (i.e., entities, materials, substances) of non-interest, in the sample of matter. Such characterization may include determining any number and types or kinds of biological, chemical, or/and physical, properties, characteristics, features, parameters, or/and behavior, of the at least one object of interest in the sample of matter.
There exists a plethora of prior art teachings and practices of a wide variety of different analytical methods and techniques, and associated analytical equipment, instrumentation, hardware, and software, which are suitable for on-line (real time, near-real time) or off-line analyzing a sample of matter. Clearly, many factors, parameters, conditions, criteria, and requirements, are involved that need to be identified, analyzed, considered, accounted for, and possibly tested, in order to properly determine which particular analytical method or technique, and, associated analytical equipment, instrumentation, hardware, and software, are most suitable, alternatively suitable, or optionally suitable, for analyzing a particular sample of matter.
Hyper-spectral imaging and analysis has been established as a highly unique, specialized, and sophisticated, combined spectroscopy and imaging type of analytical method or technique, in the more encompassing field or area of analytical science and technology, involving the sciences and technologies of spectroscopy and imaging. By definition, hyper-spectral imaging and analysis is based on a combination of spectroscopy and imaging theories, principles, and practices, which are exploitable for analyzing samples of matter in a highly unique, specialized, and sophisticated, manner.
Hyper-spectral imaging and analysis, theory, principles, and practices thereof, and, related and associated applications and subjects thereof, such as the more general subject of spectral imaging, are well known and taught about in scientific, technical, and patent, literature, and currently practiced in a wide variety of numerous different fields and areas of science and technology. Several (mostly recent) examples of such teachings and practices are disclosed in references 1-29 (and references cited therein). Selected teachings and practices of hyper-spectral imaging and analysis by the same applicant/assignee of the present invention are disclosed in references 30-36. For the purpose of establishing the scope, meaning, and field(s) or area(s) of application, and meaning, of the present invention, and in understanding problems solved by the present invention, the following background is provided.
Hyper-Spectral Imaging and Analysis
The more highly specialized, complex, and sophisticated, spectroscopic imaging technique of ‘hyper-spectral’ imaging and analysis, in contrast to the regular or standard spectroscopic imaging technique of ‘spectral’ imaging and analysis, consists of using a hyper-spectral imaging and analysis system for on-line (real time, near-real time) or off-line generating and collecting (acquiring) hyper-spectral images and spectra (herein, together, generally referred to as hyper-spectral image data and information), and, processing and analyzing the acquired hyper-spectral image data and information. In hyper-spectral imaging, multiple fields of view of a sample of matter are ‘hyper-spectrally’ scanned and imaged while the sample of matter (containing objects, and components thereof) is exposed to electromagnetic radiation. During the hyper-spectral scanning and imaging there is generating and collecting relatively large numbers (up to the order of millions) of multiple spectral (i.e., hyper-spectral) images, ‘one-at-a-time’, but, in an extremely fast or rapid sequential manner, of the objects (and components thereof) emitting electromagnetic radiation at a plurality of many wavelengths and frequencies, where the wavelengths and frequencies are associated with different selected (relatively narrow) portions or bands, or bands therein, of an entire hyper-spectrum emitted by the objects (and components thereof). A hyper-spectral imaging and analysis system can be operated in an extremely fast or rapid manner for providing exceptionally highly resolved spectral and spatial data and information of an imaged sample of matter, with high accuracy and high precision (reproducibility), which are fundamentally unattainable by using a regular or standard spectral imaging and analysis system.
In general, when electromagnetic radiation, for example, in the form of light such as that supplied by the sun, or by a man-made imaging type of illuminating or energy source, such as that used during hyper-spectral imaging, is incident upon an object, the electromagnetic radiation is affected by one or more of the biological, chemical, or/and physical, species or components making up the object, by any combination of electromagnetic radiation absorption, diffusion, reflection, diffraction, scattering, or/and transmission, mechanisms. Moreover, an object whose composition includes organic chemical species or components, ordinarily exhibits some degree or extent of fluorescent or/and phosphorescent properties, characteristics, and behavior, when illuminated by some type of electromagnetic radiation or light, such as ultra-violet (UV), visible (VIS), or infrared (IR), types of light. The affected electromagnetic radiation, in the form of diffused, reflected, diffracted, scattered, or/and transmitted, electromagnetic radiation emitted by, or/and emerging from, the object, is directly and uniquely related to the biological, chemical, or/and physical, properties, characteristics, and behavior, of the object, in general, and of the chemical species or components making up the object, in particular, and therefore represents a spectral (‘fingerprint’ or ‘signature’) pattern type of identification and characterization of the object.
Accordingly, hyper-spectral images generated by, and collected from, a sample of matter, are correlated with emission spectra of the sample of matter, where the emission spectra correspond to spectral representations in the form of spectral ‘fingerprint’ or ‘signature’ pattern types of identification and characterization, of the hyper-spectrally imaged objects (and components thereof) in the sample of matter. Such hyper-spectral image data and information are processed and analyzed by using automatic pattern recognition (APR) or/and optical character recognition (OCR) types of hyper-spectral imaging data and information processing and analysis, for identifying, characterizing, or/and classifying, the physical, chemical, or/and biological, properties, characteristics, and behavior, of the hyper-spectrally imaged objects (and components thereof) in the sample of matter.
Hyper-Spectral Imaging and Analysis of a Sample of Matter
Following provision of a sample of matter, or following obtaining or collecting a sample of matter, analyzing a sample of matter via hyper-spectral imaging and analysis, similar to analyzing a sample of matter by essentially any analytical method or technique, involves three separate, but integrated, general domains or stages of main activities and procedures. In particular, following provision of a sample of matter, or following obtaining or collecting a sample of matter, hyper-spectral imaging and analysis of the sample of matter typically involves the following three separate, but integrated, general domains or stages of main activities and procedures: (i) preparing an appropriate test form (usually, a solid or liquid form) of the sample of matter, which is suitable for being subjected to hyper-spectral imaging and analysis, (ii) generating and collecting hyper-spectral image data and information of the test form of the sample of matter, and (iii) processing and analyzing the generated and collected hyper-spectral image data and information.
In general, each of these three general domains or stages of main activities and procedures of a hyper-spectral imaging and analysis application can be characterized by various different levels or degrees of the following performance parameters: accuracy, precision (reproducibility), sensitivity, resolution, and speed. In any give hyper-spectral imaging and analysis application, the just stated three general domains or stages of main activities and procedures are fully integrated and inter-dependent upon each other.
Performance parameters of accuracy, precision (reproducibility), sensitivity, resolution, or/and speed (time scale), of the first general domain or stage of main activities and procedures of a hyper-spectral imaging and analysis application, i.e., regarding preparation of an appropriate test form of the sample of matter, affect and influence the performance parameters of accuracy, precision (reproducibility), sensitivity, resolution, or/and speed (time scale), of each of the succeeding second and third general domains or stages of main activities and procedures. More specifically, main activities and procedures of preparing an appropriate test form of a sample of matter, affect and influence generating and collecting hyper-spectral image data and information of the test form of the sample of matter, which in turn, affect and influence processing and analyzing the generated and collected hyper-spectral image data and information.
Preparing an Appropriate Test Form of a Sample of Matter
This general domain or stage of main activities and procedures of a hyper-spectral imaging and analysis application involves preparing an appropriate test form of a sample of matter which is suitable for, and compatible with, operation and use of equipment and instrumentation of a given hyper-spectral imaging and analysis system. Typically, an appropriate test form of a sample of matter involves using a relatively small quantity (for example, on the order of microliters (μl)) of the sample of matter, ‘as is’, in a solid, solution, or suspension, form. Alternatively, according to the actual composition or makeup of the sample of matter (including the objects and components thereof present in the sample of matter), an appropriate test form of a sample of matter may involve dissolving, suspending, or/and mixing, i.e., reformulating, a relatively small quantity of the sample of matter into a solution or suspension form. A portion or aliquot of the solid, solution, or suspension, test form of the sample of matter is then, typically, placed on a clean, inert, metal slide or plate, or, on a clean, inert, plastic (e.g., Teflon®) or glass microscope type slide or plate, which is suitable for functioning as a sample holder in a hyper-spectral imaging and analysis system. The slide or plate (sample holder) with the portion or aliquot of the test solution or suspension of the sample of matter is then appropriately positioned and secured (fixed) upon a three-dimensionally movable (i.e., translational), and optionally, angularly movable (i.e., rotational), examination stage or platform of the hyper-spectral imaging and analysis system.
For the purpose of fully understanding the hereinbelow described significant on-going problems and limitations of hyper-spectral imaging and analysis of a sample of matter, immediately following is a brief description of hyper-spectrally imaged scenes of a test form of a sample of matter, in terms of types, categories, or classes, of objects existing in the hyper-spectrally imaged scenes.
Hyper-Spectrally Imaged Scenes of a Sample of Matter, and Types, Categories, or Classes, of Objects Therein
In general, in hyper-spectrally imaged scenes of a test form of a sample of matter (including the objects and components thereof present in the sample of matter), the objects (i.e., entities, materials, substances) can be typed, categorized, or classified, according to two main different types, categories, or classes. Namely, ‘objects of non-interest’, and ‘objects of interest’, each of which is basically defined as follows. ‘Objects of non-interest’ correspond to objects of (present or contained in) a hyper-spectrally imaged scene of the sample of matter which are not of interest to a human operator (observer, viewer, analyzer, or/and controller) of a process involving the sample of matter. ‘Objects of interest’ correspond to objects of (present or contained in) a hyper-spectrally imaged scene of the sample of matter which are of interest to a human operator of a process involving the sample of matter. For further understanding the significantly different meanings and attributes of objects of non-interest and objects of interest, in the context of the present invention, objects of non-interest are considered as being part of the ‘background’ of, or within, a hyper-spectrally imaged scene of the sample of matter, whereas objects of interest are considered as being ‘targets’ of, or within, a hyper-spectrally imaged scene of the sample of matter. Accordingly, in hyper-spectral imaging, individual objects among a plurality, collection, or ensemble, of several objects (i.e., entities, materials, substances) of (present or contained in) a hyper-spectrally imaged scene of a sample of matter, can be typed, categorized, or classified, according to the above stated two main different types, categories, or classes, of objects, i.e., objects of non-interest (i.e., background), and objects of interest (i.e., targets).
Typically, each hyper-spectrally imaged scene of a sample of matter includes or contains a distribution of different relative numbers (i.e., ratios, proportions) of the preceding defined two main different types, categories, or classes, of objects. For example, a given hyper-spectrally imaged scene may include or contain a distribution of a relatively small number of objects of interest (targets), and a relatively large number of objects of non-interest (corresponding to a relatively high or ‘noisy’ background). Conversely, a given imaged scene may include or contain a distribution of a relatively large number of objects of interest (targets), and a relatively small number of objects of non-interest (corresponding to a relatively low or ‘quiet’ background).
Moreover, for example, there are many hyper-spectral imaging and analysis applications wherein the majority of hyper-spectrally imaged scenes include or contain a relatively ‘exceptionally’ small number of objects of interest (targets) compared to a relatively large number of objects of non-interest (high or noisy background). For example, such applications are wherein the number of objects of interest (targets), relative to the number of all objects [of interest (target) and of non-interest (background)] of (present or contained in) a hyper-spectrally imaged scene, corresponds to a ratio or proportion as low as 1% [1 part per hundred (pph)], or 10−1% [1 part per thousand (ppt)], or 10−4% [1 part per million (ppm)], 10−7% [1 part per billion (ppb)], or even as low as 10−10% [1 part per trillion (pptr)].
In addition to hyper-spectrally imaged scenes including distributions of different relative numbers (ratios, proportions) of the two main different types, categories, or classes, of objects, it is noted that each hyper-spectrally imaged object (i.e., entity, material, substance) is definable and characterizable by a set of a wide variety of numerous possible biological, chemical, or/and physical, properties, characteristics, and behavior. For example, in a given hyper-spectrally imaged scene, there may exist different relative numbers, and types kinds, of objects whose ‘hyper-spectral’ image data and information (particularly including, for example, emission spectra corresponding to spectral representations in the form of spectral fingerprint or signature pattern types of identification and characterization), are quite similar, or even nearly identical, i.e., barely distinguishable or resolvable, but whose ‘biological, chemical, or/and physical’ data and information (in terms of properties, characteristics, or/and behavior), are significantly different, and not at all similar or nearly identical, i.e., not at all easily distinguishable or resolvable, or vice versa.
Regardless of the actual distributions of the different relative numbers (i.e., ratios, proportions) of objects of interest (targets) and objects of non-interest (background) in hyper-spectrally imaged scenes of a sample of matter, any hyper-spectral imaging and analysis application ultimately involves the need for identifying, distinguishing, and resolving, the objects of interest (targets) from the objects of non-interest (background) in the hyper-spectrally imaged scenes. This involves the need for identifying, distinguishing, and resolving, the hyper-spectral image data and information of the objects of interest (targets) from the hyper-spectral image data and information of the objects of non-interest (background). Moreover, there is also the need for performing such identifying, distinguishing, and resolving, procedures and operations in relation to the biological, chemical, or/and physical data and information of the objects of interest (targets) and of the objects of non-interest (background), in the hyper-spectrally imaged scenes.
Significant on-Going Problems and Limitations of Hyper-Spectral Imaging and Analysis of a Sample of Matter
In general, significant on-going problems and limitations of hyper-spectral imaging and analysis of a sample of matter are usually based on, involve, or/and are associated with, the theoretical or/and practical difficulties and complexities that arise when performing, or attempting to perform, the previously stated three separate, but integrated, general domains or stages, (i), (ii), and (iii), of main activities and procedures, with some combination of the performance parameters of high accuracy, or/and high precision (high reproducibility), or/and high sensitivity, or/and high resolution, or/and at high speed (short time scale), be it during on-line (real time, near-real time) or off-line, in an optimum and highly efficient manner. Exceptional difficulties and complexities arise when performing, or attempting to perform, the general domains or stages, (i), (ii), and (iii), of main activities and procedures, with the ‘ultimate’ combination of the highly desirable performance parameters of high accuracy, ‘and’ high precision (high reproducibility), ‘and’ high sensitivity, ‘and’ high resolution, ‘and’ at high speed (short time scale), all at the same time (i.e., simultaneously), be it during on-line (real time, near-real time) or off-line, in an optimum and highly efficient manner.
A main source or origin of difficulties and complexities that arise when performing hyper-spectral imaging and analysis of a sample of matter is the often problematic and complicating spatially or/and temporally varying presence of objects (entities, materials, substances) of non-interest (background) in the sample of matter, directly translating to the corresponding problematic and complicating spatially or/and temporally varying presence of objects of non-interest (background) in the hyper-spectrally imaged scenes of the test form of the sample of matter. The spatially or/and temporally varying presence of objects of non-interest in the sample of matter negatively interferes, to a varying extent or degree (depending upon several interdependent factors), with the hyper-spectral imaging and analysis of the objects (entities, materials, substances) of interest (targets) in the sample of matter. Accordingly, the spatially or/and temporally varying presence of objects of non-interest (background) in the hyper-spectrally imaged scenes of the test form of the sample of matter, negatively interferes, to a varying extent or degree, with the hyper-spectral imaging and analysis of objects of interest (targets) in the hyper-spectrally imaged scenes of the test form of the sample of matter.
The preceding problematic and complicating aspects, regarding the spatially or/and temporally varying presence of objects of non-interest (background), negatively affect and influence generating and collecting hyper-spectral image data and information of the sample of matter, which in turn, negatively affect and influence processing and analyzing the generated and collected hyper-spectral image data and information. Moreover, such problematic and complicating aspects, along with the corresponding negative affects and influences, subsequently make it difficult to achieve high levels of the performance parameters of accuracy, precision (reproducibility), sensitivity, resolution, or/and speed (time scale), of an overall hyper-spectral imaging and analysis application, such as that based on analyzing a sample of matter via hyper-spectral imaging and analysis, for identifying and characterizing an object of interest in the sample.
The preceding problematic and complicating aspects, regarding the spatially or/and temporally varying presence of objects of non-interest (background), which negatively affect and influence hyper-spectral imaging and analysis of a sample of matter, are especially relevant to an application involving on-line (real time or near-real time) or off-line analyzing a sample of air (i.e., an air sample) via hyper-spectral imaging and analysis, for identifying and characterizing an object of interest (target) in the air sample. In particular, wherein such an application, the sample of air can be collected or obtained from an indoor source of air (e.g., a post office, an airport, a subway station, a shopping mall, a sports arena, or an office building) or from an outdoor source of air. In such an application, the interfering objects of non-interest (background) are the numerous different (non-target) components (i.e., entities, materials, substances) present in the air sample. In the air sample, the object of interest (target) can be a (potentially hazardous) biological agent (e.g., a bacterium [such as spore-forming bacterium Bacillus anthracis], a virus, a fungus, or a toxin), or a (potentially hazardous) chemical agent (e.g., a nerve agent [e.g., sarin, tabun, or soman], or a chemical poison [e.g., a cyanide compound, or an organophosphate compound]), which is composed or made up of organic or/and inorganic materials or substances, and is preferably in a solid (e.g., particulate) phase.
In the collected sample of air, interfering objects of non-interest (background) originate from the numerous, spatially variable (i.e., varying or changing with position or location) or/and temporally variable (i.e., varying or changing with time) different types and concentrations of (non-target) components (i.e., entities, materials, substances) present in the source of air. The indoor or outdoor source of air typically includes numerous, spatially or/and temporally variable different types and concentrations of (non-target) components, such as dust (fine, dry particles of matter), pollen (fine particulate or powderlike material consisting of pollen grains produced by plants), minerals, non-target types of biological matter (mold (fungi), bacteria), and non-target types of particulate chemical matter. Such (non-target) components in the air source can be in aerosol form, being a gaseous suspension of fine solid or liquid particles which circulate throughout the (indoor or outdoor) air source. Such (non-target) components have relative concentrations which, typically, spatially vary or change (i.e., vary or change with position and location) or/and temporally vary or change (i.e., vary or change with time), depending upon the spatial or/and temporal variations in the local atmospheric environment and weather conditions of the indoor or outdoor source of air, and depending upon the location and time at which the air sample is collected or obtained from the air source. Therefore, a plurality of air samples is expected to have such spatially or/and temporally varying (non-target) components whose relative concentrations vary in accordance with their spatial or/and temporal variation in the source of air from which the air samples are collected or obtained.
In a similar manner, an object of interest (target), such as a (potentially hazardous) biological agent (e.g., a bacterium [such as spore-forming bacterium Bacillus anthracis], a virus, a fungus, or a toxin), or a (potentially hazardous) chemical agent (e.g., a nerve agent [e.g., sarin, tabun, or soman], or a chemical poison [e.g., a cyanide compound, or an organophosphate compound]), which is present in a sample of air collected or obtained from an indoor or outdoor source of air, has a relative concentration which, typically, spatially varies or changes (i.e., varies or changes with position and location) or/and temporally varies or changes (i.e., varies or changes with time), depending upon the spatial or/and temporal variations in the local atmospheric environment and weather conditions of the indoor or outdoor source of air, and depending upon the location and time at which the air sample is collected or obtained from the air source. Therefore, a plurality of air samples is expected to have such a spatially or/and temporally varying object of interest (target) whose relative concentration varies in accordance with its spatial or/and temporal variation in the source of air from which the air samples are collected or obtained.
In such an application, typically, a given hyper-spectrally imaged scene of a test form of an air sample includes or contains a distribution of a relatively small number of the object of interest (target, for example, in the form of a spectrally marked biological or chemical agent), and a relatively large number of the objects of non-interest (high or noisy background, in the form of (non-target) components of the air sample). Moreover, in such an application, typically, the majority of hyper-spectrally imaged scenes include or contain a relatively exceptionally small number of the object of interest (target) compared to a relatively large number of the objects of non-interest (background). For example, wherein the number of the object of interest (target), relative to the number of all objects [of interest (target) and of non-interest (background)] of (present or contained in) a hyper-spectrally imaged scene, corresponds to a ratio or proportion as low as 1% [1 part per hundred (pph)], or 10−1% [1 part per thousand (ppt)], or 10−4% [1 part per million (ppm)], 10−7% [1 part per billion (ppb)], or even as low as 10−10% [1 part per trillion (pptr)].
Additionally, in such an application, in the hyper-spectrally imaged scenes of a test form of an air sample, each hyper-spectrally imaged object of interest (target, e.g., in the form of a spectrally marked biological or chemical agent) and each hyper-spectrally imaged object of non-interest (background, in the form of (non-target) components of the air sample), is definable and characterizable by a set of a wide variety of numerous possible biological, chemical, or/and physical, properties, characteristics, and behavior. For example, in a given hyper-spectrally imaged scene, there may occur the scenario wherein the object of interest (target, in the form of a spectrally marked biological or chemical agent) and objects of non-interest (background, in the form of (non-target) components of the air sample) exhibit ‘hyper-spectral’ image data and information (particularly including, for example, emission spectra corresponding to spectral representations in the form of spectral fingerprint or signature pattern types of identification and characterization), which are quite similar, or even nearly identical, i.e., barely distinguishable or resolvable, but whose ‘biological, chemical, or/and physical’ data and information (in terms of properties, characteristics, or/and behavior), are significantly different, and not at all similar or nearly identical, i.e., not at all easily distinguishable or resolvable, or vice versa.
Regardless of the actual distributions of the different relative numbers (i.e., ratios, proportions) of the object of interest (target, in the form of a spectrally marked biological or chemical agent) and the objects of non-interest (background, in the form of (non-target) components of the air sample), in the hyper-spectrally imaged scenes of the air sample, there ultimately is the need for identifying, distinguishing, and resolving, the object of interest (target, in the form of a spectrally marked biological or chemical agent) from the objects of non-interest (background, in the form of (non-target) components of the air sample) in the hyper-spectrally imaged scenes.
This involves the need for identifying, distinguishing, and resolving, the hyper-spectral image data and information of the object of interest (target, in the form of a spectrally marked biological or chemical agent) from that of the objects of non-interest (background, in the form of (non-target) components of the air sample). Moreover, there is also the need for performing such identifying, distinguishing, and resolving, procedures and operations in relation to the biological, chemical, or/and physical data and information, of the object of interest (target, in the form of a spectrally marked biological or chemical agent) and of the objects of non-interest (background, in the form of (non-target) components of the air sample) in the hyper-spectrally imaged scenes. Furthermore, there is also need for performing such identifying, distinguishing, and resolving, procedures and operations in view of the fact that the hyper-spectrally imaged scenes are generated and collected from air samples wherein the objects of non-interest (background, in the form of (non-target) components of the air sample) and the object of interest (target, in the form of a spectrally marked biological or chemical agent) have relative concentrations that vary in accordance with their spatial or/and temporal variation in the source of air from which the air samples are collected or obtained.
Accordingly, the preceding described problematic and complicating aspects, along with the corresponding negative affects and influences, due to the spatially or/and temporally varying presence of objects of non-interest (background) in a sample of air, make it difficult to achieve high levels of the performance parameters of accuracy, precision (reproducibility), sensitivity, resolution, or/and speed (time scale), of an overall hyper-spectral imaging and analysis application. This is particularly the case for an exemplary specific application involving on-line (real time or near-real time) or off-line hyper-spectral imaging and analysis of a sample of air (i.e., an air sample), for identifying and characterizing an object of interest therein, wherein such an application, the interfering objects of non-interest (background) are the numerous different spatially or/and temporally varying (non-target) components (i.e., entities, materials, substances) present in the air sample, and the object of interest (target) is a (potentially hazardous) biological agent (e.g., a bacterium [such as spore-forming bacterium Bacillus anthracis], a virus, a fungus, or a toxin), or a (potentially hazardous) chemical agent (e.g., a nerve agent [e.g., sarin, tabun, or soman], or a chemical poison [e.g., a cyanide compound, or an organophosphate compound]).
Thus, despite hyper-spectral imaging and analysis being well known and taught about in the prior art and currently practiced in a wide variety of numerous different fields and areas of science and technology, the preceding described problematic and complicating aspects, and corresponding negative affects and influences, which are caused by the spatially or/and temporally varying presence of objects of non-interest (background) in a sample of matter, such as a sample of air, which significantly limit hyper-spectral imaging and analysis of the sample of matter, continue to exist, and need to be overcome.
There is thus a need for, and, it would be highly advantageous and useful to have an invention of a method for hyper-spectral imaging and analysis of a sample of matter, for identifying and characterizing an object of interest therein. There is also need for such an invention which includes a procedure for preparing a test solution or suspension from a sample of matter, such that the test solution or suspension is particularly suitable for subjecting to hyper-spectral imaging and analysis. There is need for such an invention which is generally applicable for on-line (e.g., real time or near-real time) or off-line hyper-spectral imaging and analysis of various different types or kinds of samples of matter, wherein the matter, and at least one object of interest therein, are composed or made up of organic or/and inorganic materials or substances, which are in a solid (e.g., particulate) phase, a liquid (e.g., solution or suspension) phase, or/and a gaseous (e.g., aerosol) phase. Additionally, there is need for such an invention which provides the capability of achieving the ‘ultimate’ combination of the highly desirable performance parameters of high accuracy, ‘and’ high precision (high reproducibility), ‘and’ high sensitivity, ‘and’ high resolution, ‘and’ at high speed (short time scale), all at the same time (i.e., simultaneously), be it during on-line or off-line, in an optimum and highly efficient manner.
Furthermore, there is need for such an invention which is particularly implementable in applications involving on-line (real time or near-real time) or off-line hyper-spectral imaging and analysis of a sample of air (i.e., an air sample), for identifying and characterizing an object of interest therein, wherein the object of interest is a (potentially hazardous) biological agent (e.g., a bacterium [such as spore-forming bacterium Bacillus anthracis], a virus, a fungus, or a toxin), or a (potentially hazardous) chemical agent (e.g., a nerve agent [e.g., sarin, tabun, or soman], or a chemical poison [e.g., a cyanide compound, or an organophosphate compound]). Moreover, there is need for such an invention where the sample of air is collected or obtained (e.g., via an air sampling or collecting system) from an indoor source of air (e.g., a post office, an airport, a subway station, a shopping mall, a sports arena, or an office building) or from an outdoor source of air. Additionally, there is particular need for such an invention wherein the object of interest can be a biological agent, such as the spore-forming bacterium Bacillus anthracis, which is chemically marked (e.g., via terbium trichloride [TbCl3]), or biologically marked (e.g., via antibodies of an immunoassay technique), for enabling identification and characterization thereof via hyper-spectral imaging and analysis.